{"id":"W4412870005","doi":"10.3390/e27080811","title":"Deep Reinforcement Learning-Based Resource Allocation for UAV-GAP Downlink Cooperative NOMA in IIoT Systems","year":2025,"lang":"en","type":"article","venue":"Entropy","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China; British Columbia Innovation Council","keywords":"Noma; Reinforcement learning; Telecommunications link; Computer science; Resource allocation; Resource (disambiguation); Distributed computing; Computer network; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001177676,0.0001305563,0.0001714339,0.0001918153,0.00008580084,0.0000318557,0.0002680781,0.00009837119,0.000007224053],"category_scores_gemma":[0.0001996156,0.000137539,0.00003076804,0.0002869446,0.00003844865,0.00007058317,0.00004541282,0.0002304345,0.00001222191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003056513,"about_ca_system_score_gemma":0.00002281526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001045488,"about_ca_topic_score_gemma":0.00001566275,"domain_scores_codex":[0.9992464,0.00003870568,0.0002911604,0.0001445292,0.00008102901,0.0001981746],"domain_scores_gemma":[0.9992868,0.0001937082,0.00005107277,0.0003857359,0.00006462377,0.0000180595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000217285,0.00001182819,0.0001451284,0.0000813985,0.0000169682,3.634186e-7,0.0001081512,0.9682854,0.001615374,0.02784877,0.0002751544,0.001589719],"study_design_scores_gemma":[0.0007440879,0.00004706073,0.00008570563,0.0001144104,0.000004529396,1.501514e-7,0.0005328763,0.9558091,0.01351811,0.0001108593,0.02890665,0.000126473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005035846,0.001251582,0.9906086,0.0004866924,0.0001130669,0.000682217,0.000001172666,0.000664234,0.001156589],"genre_scores_gemma":[0.9962558,0.00008608956,0.002527128,0.00004687919,0.00001480247,0.0005401775,0.00007649805,0.00001893491,0.0004337174],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9912199,"threshold_uncertainty_score":0.5608675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119149570563426,"score_gpt":0.2486511961107714,"score_spread":0.2374597004051371,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}